autolens.AnalysisPoint#
- class AnalysisPoint[source]#
Bases:
Analysis
,AnalysisLensing
The analysis performed for model-fitting a point-source dataset, for example fitting the point-sources of a multiply imaged lensed quasar or supernovae of many source galaxies of a galaxy cluster.
The analysis brings together the data, model and non-linear search in the classes log_likelihood_function, which is called by every iteration of the non-linear search to compute a likelihood value which samples parameter space.
- Parameters
point_dict (
PointDict
) – A dictionary containing the full point source dictionary that is used for model-fitting.solver (
PointSolver
) – The object which is used to determine the image-plane of source-plane positions of a model (via a Tracer).dataset – The imaging of the point-source dataset, which is not used for model-fitting but can be used for visualization.
cosmology (
LensingCosmology
) – The cosmology of the ray-tracing calculation.settings_lens – Settings which control how the model-fit is performed.
Methods
fit_positions_for
- rtype
FitPointDict
Determine the fit of the strong lens system of lens galaxies and source galaxies to the point source data.
log_likelihood_positions_overwrite_from
Call the positions overwrite log likelihood function, which add a penalty term to the likelihood if the positions of the multiple images of the lensed source do not trace close to one another in the source plane.
make_result
modify_after_fit
Overwrite this method to modify the attributes of the Analysis class before the non-linear search begins.
modify_before_fit
Overwrite this method to modify the attributes of the Analysis class before the non-linear search begins.
modify_model
output_profiling_info
Output the log likelihood function profiling information to hard-disk as a json file.
plane_via_instance_from
Create a Plane from the galaxies contained in a model instance.
profile_log_likelihood_function
This function is optionally called throughout a model-fit to profile the log likelihood function.
save_attributes
save_results
should_visualize
Whether a visualize method should be called perform visualization, which depends on the following:
tracer_via_instance_from
Create a Tracer from the galaxies contained in a model instance.
visualize
visualize_before_fit
visualize_before_fit_combined
visualize_combined
with_model
Associate an explicit model with this analysis.
Attributes
fit_func
- rtype
- log_likelihood_function(instance)[source]#
Determine the fit of the strong lens system of lens galaxies and source galaxies to the point source data.
- Parameters
instance – A model instance with attributes
- Returns
fit – A fractional value indicating how well this model fit and the model masked_dataset itself
- Return type
Fit